The Use of Metaheuristics in the Evolution of Collaborative Filtering Recommender Systems: A Review
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-62922-8_16
Reference23 articles.
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2. Isinkaye, F.O., Folajimi, Y.O., Ojokoh, B.A.: Recommendation systems: principles, methods and evaluation. Egypt. Inform. J. 16(3), 261–273 (2015). https://doi.org/10.1016/j.eij.2015.06.005
3. Roy, D., Dutta, M.: A systematic review and research perspective on recommender systems. J. Big Data 9(1), 59 (2022). https://doi.org/10.1186/s40537-022-00592-5
4. Pu, P., Chen, L., Hu, R.: Evaluating recommender systems from the user’s perspective: survey of the state of the art. User Model. User-Adap. Inter. 22, 317–355 (2012). https://doi.org/10.1007/s11257-011-9115-7
5. Kuo, R.J., Li, S.S.: Applying particle swarm optimization algorithm-based collaborative filtering recommender system considering rating and review. Appl. Soft Comput. 20, 110038 (2023). https://doi.org/10.1016/j.asoc.2023.110038
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